Video Games with R - Interactive Graphs

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Install Packages from CRAN:

install.packages("ggplot2")
install.packages("dplyr")
install.packages("RColorBrewer")
install.packages("plotly")

Next you “activate” the packages.

library(ggplot2)
library(dplyr)
library(RColorBrewer)
library(plotly)

Loading Data

vgsales=read.csv("C:\\Users\\Prithvi Kinariwala\\Documents\\video-games-with-R\\vgsales.csv")

What years saw the greatest amount of game releases?

We take the ggplot function from the main report and pass it through a ggplotly function as a parameter.

yeargames=vgsales
yeargames<-yeargames[!(yeargames$Year=="N/A" ),]
graph1 = ggplot(data = yeargames, mapping = aes(x =Year, fill= Platform))+
  geom_bar()+
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5))+
  labs(x = "Year", y="Number of Games Published",title = "Games Published 1980-2016")

ggplotly(graph1)

Are certain gaming platforms more violent than others?

We’ll do the same data wrangling and pass the resultant ggplot as a parameter into the ggploty function.

violentgames=vgsales

# For-loop to classify certain genres as Violent and others as Non-violent
Violent = NULL
for(i in 1:nrow(violentgames))
{
    if(violentgames[i,5]=="Action"|violentgames[i,5]=="Fighting"|violentgames[i,5]=="Shooter" ){Violent[i]<-"Violent"}
    else{Violent[i]<-"Not Violent"}
}

# For-loop to classify platforms by platform manufacterers 
ConsoleMaker = NULL
for(i in 1:nrow(violentgames))
{
  if(violentgames[i,3]=="DS"|violentgames[i,3]=="3DS"|violentgames[i,3]=="GB"|violentgames[i,3]=="GBA"|violentgames[i,3]=="N64"|violentgames[i,3]=="NES"|violentgames[i,3]=="Wii"|violentgames[i,3]=="WiiU"){ConsoleMaker[i]<-"Nintendo"}
  else if(violentgames[i,3]=="PS"|violentgames[i,3]=="PS2"|violentgames[i,3]=="PS3"|violentgames[i,3]=="PS4"|violentgames[i,3]=="PSP"|violentgames[i,3]=="PSV"){ConsoleMaker[i]<-"Sony"}
  else if(violentgames[i,3]=="X360"|violentgames[i,3]=="XB"|violentgames[i,3]=="XOne"){ConsoleMaker[i]<-"Microsoft"}
  else{violentgames[-i]}
}

violentData=cbind(violentgames,Violent,ConsoleMaker)
violentData <- na.omit(violentData)

Interactive Stacked Bar Graph:

graph2A = ggplot(data = violentData, mapping = aes(x =Platform,fill= Violent)) + 
  geom_bar()+facet_wrap(~ConsoleMaker)+
  labs(y="Number of Video Games",title = "Violence in Video Games by Major Platform Making Companies")+
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5))+scale_fill_manual(values = c("steelblue1","tomato2"))

ggplotly(graph2A)

Interactive Percent Bar Graph:

graph2B = ggplot(data = violentData, mapping = aes(x =Platform,fill= Violent))+ 
  geom_bar(position="fill")+facet_wrap(~ConsoleMaker)+
  labs(y="Percent Composition",title = "Violence in Video Games by Platform Making Companies")+
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5))+scale_fill_manual(values = c("steelblue1","tomato2"))

ggplotly(graph2B)

Is PlayStation better than Xbox?

Is the proportion of PlayStation games greater than Xbox games?

vgsales2 = vgsales %>%
  mutate(Xbox_or_Playstation = ifelse(grepl("X", Platform), "Xbox", ifelse(grepl("PS", Platform), "PlayStation", NA)))

vgsales2 = vgsales2[-(which(vgsales2$Platform == "PCFX")),]
vgsales3 = vgsales2[-(which(vgsales2$Platform == "PSP" | vgsales2$Platform == "PSV")),]
vgsales4 = na.omit(vgsales3)

graph3 = ggplot(vgsales3, aes(x = Xbox_or_Playstation)) + geom_bar(fill = brewer.pal(3, "Set1"))+labs(y="Count", x="Console" ,title = "Video Games per Platform")

ggplotly(graph3)

Are North American or Japanese sales better at indicating how a video game does globally?

NA/Global Sales Scatterplot:

graph4A = ggplot(data = vgsales, mapping = aes(x = NA_Sales, y =Global_Sales))+   
  geom_point(alpha=0.25)+
  labs(x = "North America Sales (million)",y="Global Sales (million)",title="Global Sales by North American Sales")+
  geom_smooth(method = "lm", se = FALSE)

ggplotly(graph4A)

JP/Global Sales Scatterplot:

graph4B = ggplot(data = vgsales, mapping = aes(x = JP_Sales, y =Global_Sales))+   
  geom_point(alpha=0.25)+
  labs(x = "Japan Sales (million)",y="Global Sales (million)",title="Global Sales by Japanese Sales")+
  geom_smooth(method = "lm", se = FALSE)

ggplotly(graph4B)